UAV-Aided Indoor Localization of Emergency Response Personnel.

Unmanned aerial vehicle (UAV) aided communication systems have been gaining attention due to their wide applications in public service, military sectors, and emergency services as well as their flexibility in deployment. In this paper, we propose using 5G positioning techniques and collaborative localization to accurately estimate the locations of first responders located inside the building using outdoor UAV-mounted base stations (BSs) serving as anchors. For this setup, we perform a comprehensive Cram ' er-Rao lower bound (CRLB) based analysis to evaluate the performance of position estimation in 3D and to examine the sensitivity of the localization performance to different system parameters. Our analysis considers various system parameters: dynamic line-of-sight (LOS)/non-line-of-sight (NLOS) characteristics of the channel, geometry of the anchors, number of anchors, number of LOS anchors, NLOS bias between an anchor and a target node, and between target nodes, anchor location uncertainty, and synchronization errors among anchors. Our analysis uses time-difference-of-arrival (TDOA), and timeof-arrival (TOA) based positioning methods assuming both LOS and NLOS propagation. Through our analysis, we identify the system parameters that most significantly impact the localization performance as well as the scenarios that provide location accuracy or position error bound (PEB) on the order of 2m and 3m.